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Canadian Hog Supply Respose: A Provincial Level Analysis

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  • Rude, James
  • Surry, Yves

Abstract

Canada’s hog sector has faced two decades of tumultuous growth, yet there are no recent estimates of supply response. A state-space model for hog supply response is developed that accounts for the time series properties of the data while accounting for a multiplicity of unspecified sources for structural change. A GARCH process is used to estimate expected price and price volatility to investigate the role of price risk. Surprisingly,the results indicate relatively inelastic own price elasticities that are consistent with prior studies conducted over more stable periods. This implies that price variations can have substantial effects on total profits and losses. The lack of sensitivity of quantities supplied can be explained in Quebec by the presence of the ASRA program. In other provinces, we conjecture that price expectations used by farmers are quite diffuse and that marginal changes in the mean (and variance) do not have much impact. The effects of risk for supply response appear quite muted and impacts of feed price risk are potentially bigger than hog price risk.

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Paper provided by Structure and Performance of Agriculture and Agri-products Industry (SPAA) in its series Working Papers with number 148590.

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Date of creation: Feb 2013
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Handle: RePEc:ags:spaawp:148590

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Web page: http://servsas.fsaa.ulaval.ca/index.php?id=12482&L=1

Related research

Keywords: supply response; Kalman filter; ARCH and GARCH models; Livestock Production/Industries; Production Economics; Risk and Uncertainty; Q11; Q13; and C32;

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  1. Harvey, Andrew, 1997. "Trends, Cycles and Autoregressions," Economic Journal, Royal Economic Society, vol. 107(440), pages 192-201, January.
  2. Jalles, Joao Tovar, 2009. "Structural Time Series Models and the Kalman Filter: a concise review," FEUNL Working Paper Series wp541, Universidade Nova de Lisboa, Faculdade de Economia.
  3. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
  4. Andrew C Harvey & Andrew Scott, 1994. "Seasonality in Dynamic Regression Models," CEP Discussion Papers dp0184, Centre for Economic Performance, LSE.
  5. Mussell, Al, 2003. "PRICE DISCOVERY MECHANISMS AND ALTERNATIVES FOR CANADIAN AGRICULTURE; Part III: Applying Pricing Mechanisms," Miscellaneous Publications 18111, George Morris Center.
  6. K. D. Meilke & A. C. Zwart & L. J. Martin, 1974. "North American Hog Supply: A Comparison Of Geometric And Polynomial Distributed Lag Models," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 22(2), pages 15-30, 07.
  7. Diebold, Francis X. & Pauly, Peter, 1988. "Endogenous risk in a portfolio-balance rational-expectations model of the Deutschemark-Dollar rate," European Economic Review, Elsevier, vol. 32(1), pages 27-53, January.
  8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  9. Gervais, Jean-Philippe & Lambert, Remy, 2010. "The Simple Economics of Hog Marketing Reforms in Quebec," Working Papers 102014, Structure and Performance of Agriculture and Agri-products Industry (SPAA).
  10. Rezitis, Anthony N. & Stavropoulos, Konstantinos S., 2009. "Modeling Pork Supply Response and Price Volatility: The Case of Greece," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 41(01), April.
  11. Moschini, GianCarlo & Holt, Matthew, 1992. "Alternative Measures of Risk in Commodity Supply Models: An Analysis of Sow Farrowing Decisions in the United States," Staff General Research Papers 11252, Iowa State University, Department of Economics.
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